Abstract
Integration and maintenance of gradient acoustic information in spoken language processing
The Journal of the Acoustical Society of America, Vol.140(4 Supplement), pp.3216-3216
10/2016
DOI: 10.1121/1.4970132
Abstract
Models of speech processing seek to explain how continuous acoustic input is mapped onto discrete symbols at various levels of representation, such as phonemes, words, and referents. While recent work has supported models that posit maintenance of fine-grained information, it is not clear how continuous, low-level information in the speech signal is integrated with discrete, higher-level linguistic information. To investigate this, we created acoustic continua between the pronouns “he” and “she” by manipulating the amplitude of frication in the initial phoneme. Using the visual world eye-tracking paradigm, listeners viewed scenes containing male and female referents and heard sentences containing a pronoun, which later disambiguated to a single referent. Measures of eye-gaze revealed immediate sensitivity to both graded acoustic information and discourse-level information. Moreover, when listeners made an initially incorrect interpretation of the referent, recovery time varied as a function of acoustic step along the pronoun continuum, showing that graded acoustic information was maintained over at least a five-word delay. The results suggest that not only are listeners highly sensitive to fine-grained acoustic information in the speech signal but also that non-categorical representations are used to guide linguistic interpretation for extended periods of time.
Details
- Title: Subtitle
- Integration and maintenance of gradient acoustic information in spoken language processing
- Creators
- James B. Falandays - Villanova UniversityJoseph Toscano - Villanova UniversitySarah Brown-Schmidt - Vanderbilt University
- Resource Type
- Abstract
- Publication Details
- The Journal of the Acoustical Society of America, Vol.140(4 Supplement), pp.3216-3216
- DOI
- 10.1121/1.4970132
- ISSN
- 0001-4966
- eISSN
- 1520-8524
- Number of pages
- 1
- Date published
- 10/2016
- Academic Unit
- Psychological and Brain Sciences
- Record Identifier
- 9984632142802771
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